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AI Engineer

Remote · Brazil Full-time

About the Role

We're looking for an AI Engineer to design, build, and scale the systems that power our AI-driven product. You'll work at the intersection of large language models, multi-agent systems, and production software, turning cutting-edge AI capabilities into reliable, user-facing experiences.

What You'll Do

  • Design and implement LLM-powered pipelines, including prompt engineering, context management, and response synthesis
  • Build and optimize multi-agent orchestration systems where AI components interact, reason, and produce coherent outputs
  • Develop and maintain integrations with foundation model APIs (Anthropic, OpenAI, and others), managing latency, cost, and reliability at scale
  • Implement retrieval-augmented generation (RAG) and memory systems for persistent, context-aware behavior
  • Partner with the Evaluation/QA Engineer to build frameworks that measure output quality, coherence, and factual grounding
  • Collaborate with product and design to translate workflows into robust technical experiences
  • Ship production features across the stack, from the model layer to the application

Monitor, debug, and improve system performance, token efficiency, and guardrails

  • 3+ years of software engineering experience, with hands-on work building LLM-powered applications
  • Strong proficiency in Python and/or TypeScript/JavaScript
  • Experience with LLM APIs, prompt engineering, and agentic frameworks (e.g., LangChain, LlamaIndex, or custom orchestration)
  • Familiarity with vector databases and RAG architectures (Pinecone, Weaviate, pgvector, etc.)
  • Understanding of multi-agent systems, tool use, and function calling
  • Experience designing evaluation and testing strategies for non-deterministic AI outputs
  • Solid grasp of API design, async processing, and scalable backend architecture
  • Comfort working in a fast-moving, ambiguous, early-stage environment
  • Experience with real-time streaming (WebSockets, SSE) for conversational interfaces
  • Background in fine-tuning, model distillation, or inference optimization
  • Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD
  • Contributions to open-source AI projects

Originally posted on

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